US 2011/0071404 A1 discloses a computer-based system for evaluating a region of a lumen. The system comprises an image acquisition device for collecting a set of data regarding a lumen of a length L, wherein the set comprises a plurality of cross-sectional areas at a plurality of positions along the length L. The system further comprises a memory for storing the set of cross-sectional areas at the plurality of positions along the length L and a processor in communication with the memory, wherein the processor is configured to determine a vascular resistance ratio for the length L of the lumen in response to at least a portion of the set of data in the memory and to determine a characteristic of at least a portion of the region disposed along the length L in response to the vascular resistance ratio.
Fractional flow reserve (FFR) is a technique that involves determining the ratio between the maximum achievable blood flow in a diseased coronary artery and the theoretical maximum flow in a normal coronary artery. Currently, FFR is measured invasively during a conventional coronary angiography procedure by placing a pressure measuring wire directly in the patient's coronary arterial tree. In contrast, several newer studies have shown that a non-invasive measurement of FFR also referred to as virtual FFR or simply vFFR is possible using angiographic image data (see, e.g., Koo B K et al., “Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study”, in Journal of the American College of Cardiology, Vol. 58, No. 19, November 2011, pages 1989-1997).
The measurement of vFFR is based on the calculation of blood flow parameters, in particular, pressures resp. ratios thereof, along the segmented coronary arterial tree and, as such, depends very strongly on the accurate detection and segmentation of the coronary arteries. The problem is that such segmentation can be a very time-consuming procedure, which typically involves semi-automatic image processing algorithms that require interactive control by an operator, e.g., a physician, in order to segment each branch of the coronary arterial tree. In particular, the very thin apical arterial locations are hard to accurately segment; yet, they may be of high importance for the vFFR accuracy. In addition, operators often only rely on their visual assessment for deciding when the segmentation is “good enough”. This may lead to the missing of intermediate-grade, but clinically relevant stenoses (i.e., abnormal narrowings or constrictions of the diameter of a blood vessel) in the coronary arteries.